twCoefLogitnormN: twCoefLogitnormN

Description

Estimating coefficients from a vector of quantiles and percentiles (non-vectorized).

Usage

twCoefLogitnormN(quant, perc = c(0.5, 0.975), 
    method = "BFGS", theta0 = c(mu = 0, sigma = 1), 
    returnDetails = FALSE, ...)

Value

named numeric vector with estimated parameters of the logitnormal distribution. names: c("mu","sigma")

Arguments

quant: the quantile values
perc: the probabilities for which the quantiles were specified
method: method of optimization (see optim)
theta0: starting parameters
returnDetails: if TRUE, the full output of optim is returned instead of only entry par
...: further parameters passed to optim, e.g. control = list(maxit = 1000)

Author

Thomas Wutzler

Examples

Run this code

# experiment of re-estimation the parameters from generated observations
thetaTrue <- c(mu = 0.8, sigma = 0.7)
obsTrue <- rlogitnorm(thetaTrue["mu"],thetaTrue["sigma"], n = 500)
obs <- obsTrue + rnorm(100, sd = 0.05)        # some observation uncertainty
plot(density(obsTrue),col = "blue"); lines(density(obs))

# re-estimate parameters based on the quantiles of the observations
(theta <- twCoefLogitnorm( median(obs), quantile(obs,probs = 0.9), perc = 0.9))

# add line of estimated distribution
x <- seq(0,1,length.out = 41)[-c(1,41)]	# plotting grid
dx <- dlogitnorm(x,mu = theta[1],sigma = theta[2])
lines( dx ~ x, col = "orange")